Changes in climate have extended the snow-free season, increasing variability of forestry road conditions due to alternating periods of freezing, drying, and rainfall. Skogkurs recognized the need for a digital tool to assess and forecast road trafficability. This thesis presents a prototype system for fully digital modeling of forestry road load-bearing capacity under varying conditions throughout the year. The system is implemented as a web application that visualizes trafficability of Norwegian forestry roads based on environmental factors such as soil moisture, frost depth, and superficial deposits. The solution classifies road conditions using a traffic-light model and integrates geospatial and meteorological data to display both current and forecast trafficability up to nine days ahead. The system consists of a backend with a RESTful API and a frontend built with OpenLayers for map-based visualization. Stakeholder feedback confirms the prototype's feasibility and effectiveness as a foundation for a future operational system in the forestry industry.
This project was graded a B. See NTNU Open for the published thesis.
All repositories under this organization reflect their state at the time of delivery, check forks (1, 2) for eventual updates.
- 👑 Erik Bjørnsen 🚀
- 💪🏻 Simon Houmb 🥇
